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» Classification of microarray data using gene networks
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BMCBI
2005
212views more  BMCBI 2005»
14 years 11 months ago
PAGE: Parametric Analysis of Gene Set Enrichment
Background: Gene set enrichment analysis (GSEA) is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes i...
Seon-Young Kim, David J. Volsky
BMCBI
2010
172views more  BMCBI 2010»
14 years 12 months ago
Comparison of evolutionary algorithms in gene regulatory network model inference
Background: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineeri...
Alina Sîrbu, Heather J. Ruskin, Martin Crane
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BMCBI
2010
91views more  BMCBI 2010»
14 years 12 months ago
Algorithm-driven Artifacts in median polish summarization of Microarray data
Background: High-throughput measurement of transcript intensities using Affymetrix type oligonucleotide microarrays has produced a massive quantity of data during the last decade....
Federico M. Giorgi, Anthony M. Bolger, Marc Lohse,...
PRL
2006
130views more  PRL 2006»
14 years 11 months ago
Efficient huge-scale feature selection with speciated genetic algorithm
With increasing interest in bioinformatics, sophisticated tools are required to efficiently analyze gene information. The classification of gene expression profiles is crucial in ...
Jin-Hyuk Hong, Sung-Bae Cho
BMCBI
2007
149views more  BMCBI 2007»
14 years 11 months ago
Robust imputation method for missing values in microarray data
Background: When analyzing microarray gene expression data, missing values are often encountered. Most multivariate statistical methods proposed for microarray data analysis canno...
Dankyu Yoon, Eun-Kyung Lee, Taesung Park